Finite- and Fixed-Time Cluster Synchronization of Nonlinearly Coupled Delayed Neural Networks via Pinning Control
Xin Zhang, Wuneng Zhou, Hamid Reza Karimi, Yuqing Sun
Abstract
In this article, the cluster synchronization problem for a class of the nonlinearly coupled delayed neural networks (NNs) in both finite- and fixed-time cases are investigated. Based on the Lyapunov stability theory and pinning control strategy, some criteria are provided to ensure the cluster synchronization of the nonlinearly coupled delayed NNs in both finite-and fixed-time aspects. Then, the settling time for stabilization that is dependent on the initial value and independent of the initial value is estimated, respectively. Finally, we illustrate the feasibility and practicality of the results via a numerical example.
Topics & Concepts
Settling timeSynchronization (alternating current)Control theory (sociology)Cluster (spacecraft)Artificial neural networkLyapunov stabilityComputer scienceStability (learning theory)Class (philosophy)Initial value problemLyapunov functionControl (management)MathematicsTopology (electrical circuits)Nonlinear systemArtificial intelligencePhysicsMathematical analysisControl engineeringEngineeringStep responseMachine learningProgramming languageCombinatoricsQuantum mechanicsNeural Networks Stability and SynchronizationAdvanced Memory and Neural ComputingDistributed Control Multi-Agent Systems